Abstract:

The focus of this study is the effective prioritization of customer requirements in
collaborative product development. The CR priorities are often retrieved by
questioning and interviewing targeted customers. But the targeted customer
might not always be easily questioned, because they might not always be
obvious or clearly known. If customers might be known, they might not be able
to distinct the priorities for CR's, because everything is important to them.
Moreover concerns of the developer's organization and the society might not get
the necessary attention and it might be asked too much from the customer to
trade off all customer requirements (CR's) by their own. Because the resources
for an extensive customer interviewing might lack anyway the stakeholders
might prioritize the CR's on their own.
Efforts have already been undertaken to support cross-functional stakeholder
groups in finding priorities of CR's. Most of the investigated methods lacked the
ability to distinct the importance of CR's by a relative amount or were not able
to integrate the interdependency of stakeholders in other ways than a tiresome
negotiation processes. With the proposed Urn-Scheme approach the
stakeholders register their own individual priorities based on their perceptions of
what the relative priorities of the CR's might be. Furthermore the method
supports the stakeholders in considering the opinions of all other stakeholders.
The extent of taking others and own opinion into account is based on quantified
social interdependencies, i.e. in this study measured trust and trustworthiness
into the capability of every voter to understand costumers' perceived desired
product quality. The summed up trustworthiness in prioritizing CR's of every
stakeholder is used in a further step to finally transform the individual priorities
to relative priorities of CR's from the whole group.
With the amplification of votes from the stakeholders, who are trusted to
prioritize better than others, an improvement of the decision making process will
be achieved. A careful developed, easily to understand mathematical framework
builds the fundament for manifold analysis of the obtained voting results, e.g.
consensus analysis, priority significance check. Moreover the framework makes
the proposed method transparent and the obtained results well documented for
later reference.